cpu: rv64: matmul: fix column-major weights transpose bug

src/cpu/rv64/rvv_matmul.cpp

@@ -50,6 +50,7 @@ status_t rvv_matmul_t::execute(const exec_ctx_t &ctx) const {
     const dim_t M = pd()->M_;
     const dim_t K = pd()->K_;
     const dim_t N = pd()->N_;
+    const bool weights_col_major = pd()->weights_col_major_;
 
     // row-major [M, K] / [M, N] are reinterpreted as column-major matrices and
     // mapped to GEMM as:
@@ -62,12 +63,14 @@ status_t rvv_matmul_t::execute(const exec_ctx_t &ctx) const {
     //     column-major [K, M] with leading dim K, so transb = 'N', ldb = K.
     //   - C is viewed as column-major [N, M] with leading dim N, which matches
     //     row-major [M, N] in memory.
-    char transa = 'N';
+    char transa = weights_col_major ? 'T' : 'N';
     char transb = 'N';
     dim_t M_gemm = N;
     dim_t N_gemm = M;
     dim_t K_gemm = K;
-    dim_t lda = N; // weights: row-major [K, N] -> col-major [N, K]
+    // weights: col-major [K, N] uses leading K; row-major [K, N] is equivalent
+    // to col-major [N, K] so leading dim is N.
+    dim_t lda = weights_col_major ? K : N;
     dim_t ldb = K; // src: row-major [M, K] -> col-major [K, M]
     dim_t ldc = N; // dst: row-major [M, N] -> col-major [N, M]
     float alpha = 1.0f;

src/cpu/rv64/rvv_matmul.hpp

@@ -170,6 +170,7 @@ struct rvv_matmul_t : public primitive_t {
             M_ = src_dims[ndims - 2];
             K_ = src_dims[ndims - 1];
             N_ = wei_dims[wei_ndims - 1];
+            weights_col_major_ = is_col_major(weights_mdw);
 
             dim_t weights_batch_size = 1;
             for (int i = 0; i < wei_ndims - 2; ++i)
@@ -182,6 +183,7 @@ struct rvv_matmul_t : public primitive_t {
         dim_t K_ = 0;
         dim_t batch_ = 0;
         bool weights_are_broadcast_ = false;
+        bool weights_col_major_ = false;
     };
 
     rvv_matmul_t(const pd_t *apd) : primitive_t(apd) {}